The present invention relates to a multi-pulse coding system, and more particularly, to a multi-pulse coding system capable of realizing high-quality speech processing at low bit rates with a small amount of arithmetic operations.
The multi-pulse coding system, in which exciting source information of speech to be analyzed (input speech) is expressed by a plurality of pulses, i.e., by multi-pulses, has been known and used because of its capability of realizing high-quality coding. The fundamental concept of this system is described, for instance, on Pages 614 to 617 of "A New Model of LPC Excitation for Producing Natural-Sounding Speech at Low Bit Rates", Bishnu S. Atal and Joel R. Remde, Proc. ICASSP 1982. A method for searching the multi-pulse with high efficiency has been proposed by Araseki et al, in a paper entitled "Multi-Pulse Excited Speech Coder Based On Maximum Crosscorrelation Search Algorithm", Proc. Global Telecommunication 1983, on pages 794 to 798.
In the multi-pulse search, an acoustic weighting filter is utilized for improving an acoustic S/N ratio of the synthesized speech than the actual (physical) S/N ratio. This technique is called "noise shaping". A well-known arrangement for the noise shaping is such that the acoustic weighting filter having a transfer function given by the formula (1) is provided on the input side of a multi-pulse searcher (or coder) at the transmitting side (analysis side), and a filter having the reversed transfer function to that of the filter at the analysis side are provided on the output side of a multi-pulse decoder at the receiving-side (synthesis side). ##EQU1## where .alpha..sub.i is .alpha. parameter defined as an LPC coefficient, P; the degree of the LPC coefficient to be developed and .gamma.; the weighting coefficient whose value ranges 0&lt;.gamma.&lt;1.
In FIG. 1, #2 represents a spectrum exhibiting a frequency characteristic, expressed by the formula (1), of the acoustic weighting filter disposed at the transmitting side, and #5 denotes a spectrum exhibiting the frequency characteristic (reversed characteristic of #2) of the filter at the receiving side. An input speech indicated by a spectral characteristic #1 is subjected to the acoustic-weighting processing through the above-mentioned filter at the transmitting side to develop a signal represented by a spectal characteristic #3. The multi-pulse is obtained by a known technique on the basis of thus acoustic-weighted signal, coded and then transmitted via a transmission channel to the receiving side. The coded signal includes white quantizing noises indicated by #4. The received signal is decoded on the receiving side and thereafter subjected to an inverse acoustic-weighting processing through the receiving filter. This decoding process includes the restoration of the multi-pulse and the reproduction of the speech replica through the synthesis filter. The decoded signal, containing the white noises represented by a spectral characteristic #4, is subjected to the inverse acoustic-weighting processing, whereby the speech signal having the spectral characteristic #1 is restored. In this way, the quantizing noises are related with the spectral characteristic of the input speech. As is obvious from FIG. 1, the electric power level of speech consequently exceeds that of noises at all frequency range, thus realizing noise-masking. As a result, the S/N ratio is virtually improved, and so-called "noise shaping effect" is achievable. The numerator of the right side in the formula (1) indicates an inverse characteristic of the frequency transfer characteristic expressed by ##EQU2## which corresponds to the spectral envelope of the input speech signal, and functions levelling the spectral envelope of the input speech. The denominator of the right side member in the formula (1) indicates the frequency transfer characteristic having frequency poles coincident with the central frequencies of a plurality of frequency poles obtained by analyzing the input speech signal. .gamma. is the coefficient to be multiplied by the LPC coefficient to reduce the arithmetic operation time required for the multi-pulse development. The bandwidth of the frequency pole, as is well-known, depends upon .gamma.. For instance, when .gamma.=1.0, the bandwidth coincides with that of the frequency pole in the spectral envelope of the input speech signal. Where .gamma.&lt;1.0, the bandwidth is broader than that of the frequency pole in the spectral envelope of the input speech signal. The bandwidth monotonously increases in proportion as .gamma. approximates to 0. The frequency transfer characteristic of the speech signal which has passed through the filter (filter characteristic w(z)) may be therefore expressed by ##EQU3## This indicates that there performs enlarging and levelling the bandwidth there performs enlarging and levelling the bandwidth of the frequency pole of the spectral characteristic ##EQU4## which is acquired by analyzing the input speech signal. A duration time of the impulse response is shorter than that of the filter controlled by the LPC coefficient developed by analyzing the input speech signal, which is established by experience. For example, in many cases the virtual duration time of impulse response of the synthesis filter based on the LPC coefficient .alpha..sub.i exceeds 100 msec. On the other hand, the duration time of impulse response of the synthesis filter based on .gamma..sub.i .multidot..alpha..sub.i is hardly exceed 5 msec when .alpha.=0.8.
As described above, the duration time of impulse response of the synthesis filter decreases by using the acoustic-weighting process with the attenuation coefficient .gamma.. Shortening the impulse response duration time, however, requires more number of multi-pulses to acquire the good synthesized speech quality. This is the great hindering factor from realizing low bit rate coding. On the other hand, when searching the multi-pulse without performing the acoustic-weighting process, the impulse response length (duration) increases. This duration time increase makes it possible to approximate the input speech waveform with a small number of multi-pulses. On the contrary, however, a considerable increment in amount of the arithmetic operations is caused. In the technique, proposed by Araseki et al, for determining the multi-pulse on the basis of a crosscorrelation coefficient between the input speech waveform and the impulse response waveform of the synthesis filter, it is necessary to sequentially obtain a sum of products of the two sampled data of such waveforms. Therefore, the number of operations to obtain the sum of products increases as the impulse response time increases.